Parameters Estimation of Fractional Order System with Dominant Pole Using Co-evolutionary Particle Swarm Optimizzation (cpso) Algorithm

This paper deals with fractional order systems parameters estimation by use of Co-evolutionary Particle Swarm Optimization (CPSO) method. in some cases such as fractional order systems identification in spite of existing different methods, it is difficult to obtain estimation of model structure parameters and generally it leads to solving the with constrained complex non-linear optimization problems and this topic is one of the identification challenges of these systems. Since some of systems are inherently fractional order and because of having special behavior in these systems which in its similar integer order systems are not found. There for necessity of fractional modeling is double for such systems. In this paper, at first, we assume that the measured out-input data exists and for approximation to reality is considered that these data has been corrupted with noise. Then considering model structure as the linear combination of fractional orthogonal basis functions by use of CPSO suitable algorithm leads to estimation of fractional order system parameters and related to the complexity level of master system, suitable or acceptable approximation is obtained. In finally, by simulating of physical-typical sample system in noisy conditions leads to system identification which gained results shows the effectiveness of presented method.